Wireless Multihop Networks

Topic overview

My main research activities fall in the domain of Wireless multihop (distributed) networks, more specifically ad hoc and sensor networks. These networks pose interesting challenges due to several specificities.

The nodes in these networks communicate through a wireless channel, usually accessed through a random procedure (CSMA/CA e.g.). The MAC layer has a primary role in the network performance, as the medium is shared between several nodes. Moreover, as nodes are spread over a large geographic area, the channel access conditions differ across the network. All protocols should be ready to adapt to heterogeneous densities.

These networks are fully distributed. The network cannot rely on a particular central point to take decisions or to propagate information in a reasonable amount of time. Information, including control data, needs to be kept as local as possible.

These networks are supposed to be composed by a large number of nodes, thus scalability is an issue, especially when end-to-end communication is necessary.

The nodes often function over a limited energy reserve and communication is one of the main sources of energy expenditure.

The nodes are sometimes mobile, therefore the topology of the network changes frequently. This either requires a topology-independent set of protocols, or a frequent update of the topology discovery process.

Research directions

Concerning the applications of wireless sensor networks, I am currently looking at road traffic control through a wireless sensor network. As wireless sensors are cheaper than magnetic loops, a wireless sensor network can monitor a city’s traffic with a finer resolution. This data can, in turn, influence the traffic control devices (traffic lights, speed limits, etc.) to better regulate road traffic. In addition to all the interdependencies problems, using low-cost devices also means that measurement accuracy is low and this imprecision shall be taken into account in the control algorithms.

I am also interested in finding the correct way to implement a publish/subscribe system on a wireless sensor network. Publish/subscribe is an asynchronous communication mode in which information publishers (i.e. the sensors) do not send directly their data to the information consumers, but to an intermediate node, a broker. The broker is then in charge of dispatching the data to the interested clients (the subscribers) who expressed their interest in certain types of data. The brokers allow publishers and subscribers to ignore their mutual identities and location, easing the network management tasks. I am interested in the formation of the brokers overlay. How many brokers are necessary and where should they be located to optimize performance, energy consumption, memory usage, etc. of the various nodes? Which distributed algorithm selects the best brokers overlay?

I am also interested in distributed, calibration-less and opportunistic indoor localization. Nodes of a wireless multihop network can collaborate together to estimate their (relative or absolute) positions without requiring a specific positioning device. In an indoor scenario, using radio signals to estimate distances between nodes requires to evaluate the propagation conditions, which is difficult without calibration. To achieve this goal, we are currently looking at:

collaborative estimation of the wireless channel parameters (i.e. how close nodes can exchange information to tune a generic propagation model),

opportunistic, multi-technologies localization (i.e. a terminal equipped with Wi-Fi, GSM and Bluetooth interfaces may acquire general information on its environment by combining technology-specific information)

the use of mobility in the acquisition of channel parameters, which relates to SLAM (Simultaneous Localization and Mapping) problems.

I have been particularly interested in MAC sub-layer aspects, as it directly influences the performance one may expect from the network. The MAC sub-layer is, in this context, responsible for finding and enforcing the correct compromise between raw performance, fairness and energy consumption, which are contradictory objectives in several practical situations.

Smart cities and distributed control of urban vehicular traffic

Urban road networks have many similarities with communication networks. For example, the performance models used by both communities are close (e.g. queueing theory, cellular automata). However, unlike communication networks, whose behavior can easily be distributed, road traffic control is generally centralized and performed by human operators from an urban control center. A distributed approach has many advantages when it comes to reacting quickly to situations in a large-scale infrastructure. Its application in urban networks should allow the infrastructure to help solve local problems, for example using a reactive control of traffic lights. We have evaluated distributed algorithms to control traffic lights using the imprecise and incomplete information provided by a sensor network. In Sébastien Faye’s Ph.D, we have shown that simple algorithms are able to reduce the average waiting time of users at an intersection and to avoid starvation. We compared these strategies to state of the art proposals and to static green lights schedules used by the city of Amiens, France. We have interconnected an urban simulator (SUMO) with a communication simulator (Omnet++ / Castalia) in order to characterize the communication load in the sensor network and the effect of losses and delays on the traffic control and proposed an appropriate interpolation algorithm to compensate missing data. To increase our scenario database, we wanted to be able to generate random graphs that corresponded to actual cities maps. To find the correct type of random graphs, we modeled the deployment of control and monitoring devices at the intersections of a city and characterized the resulting graph of 50 real city maps extracted from OpenStreetMaps. We started looking at a generalization of these results by considering multiple sources and destinations of the information. Julian Garbiso’s Ph.D objective was to consider vehicles and smartphones as valid data sources, able to measure the speed, position as well as other parameters. Julian’s work consists in building an algorithm that will allow each data source to decide, locally, whether it should send its information, to whom (control center, other vehicles up to a certain distance, ..) and whether it should delay the transmission or not based on its perception of the context (urban network congestion, communication network state, position, …). The resulting middleware, that is still under development, should borrow from our works on asynchronous communication.

Distributed wireless localization

Finding the position of a mobile node in an infrastructure or a network usually relies on ranging techniques. These techniques, at the base of GPS, estimate the distance of the mobile to a set of landmarks, i.e. fixed points whose position is known. These distances are then used in a simple planar or 3D geometric model to find the node’s position. For cheap devices such as wireless sensors, ranging is based on radio signals attenuation in the environment. However, this metric has proven to be a poor distance estimator, especially in an indoor context, because of multipath fading and shadowing effects. Using simple connectivity information instead can yield to a fair precision: if two nodes are capable of communication, their distance is inferior to the communication range with high probability. We had shown in 2006 that achieving a good precision from the connectivity graph required a lot of landmarks, though. In N’deye Amy Dieng’s Ph.D thesis, we decided to revisit radio ranging using parametric radio propagation models such as the log-normal shadowing model and data analysis techniques. We first performed a large set of indoor experiments and applied a biased maximum likelihood estimator to remove irrelevant measurements in a measurements set. We noticed that localization could be improved by filtering not only the outliers values, but also some links whose propagation parameters differ from the other ones and proposed an online algorithm that yields to notable improvements in localization accuracy. Upcoming devices are expected to be equipped with IR-UWB interfaces which allow a far more precise ranging by evaluating precisely the radio signal time of flight. However, this method is very sensitive to obstructions, that’s why we evaluated the performance of extended Kalman filters.

Asynchronous communications in sensor networks

Energy is usually considered as the critical resource in sensor networks, even though memory and bandwidth are scarce too. Radio communication is a major source of energy consumption and reducing the volume of redundant or useless traffic in these networks helps increasing their lifetime. Another strategy consists in letting the nodes switch off their radio interface when they are not supposed to send, receive, or forward traffic. From the network layer’s point of view, the network topology is therefore not stable unless the sleeping periods are well aligned. Achieving and maintaining such synchronization is hard because the multiple interactions between the links lead to a large optimization problem. Practical solutions like CoAP favor shorter exchanges to long sessions, which allows building routes on-demand. The publish/subscribe communication model introduces intermediate nodes, {\em brokers}, that can store, compress, aggregate, cipher or sign data when it is produced, and transmit it to interested receivers only when they request it. In addition to introducing breakpoints that reduce the average route length, the sensors do not need to know the destination nodes addresses. They can simply keep track of a single broker’s identity, or use an anycast-like mechanism. The brokers overlay architecture has, however, a strong impact on the global performance of the network. Too many brokers generate an important volume of control traffic for synchronization and too few brokers create bottlenecks. We studied the ideal locations of these brokers in a wireless sensor network using a queueing model. With extensive simulation, we compared the performance of various selection criteria based on graph centrality measures in terms of energy consumption, queues sizes, publications delivery times and maximum load that the network can sustain. Rémy Léone’s Ph.D extended this work by examining how caches located on the network gateways should behave. Indeed, in the classical scenario, the wireless sensor network is orchestrated by one or few gateways that are at least intermediates in all applicative traffic. It is therefore a natural choice for a cache and a level-1 broker in a global publish/subscribe architecture. Besides, it has the capability to estimate, from the excerpt of the traffic it sees, how much energy remains in the different network zones and adapt the caching behavior and the in-network brokers location and behavior. We have compared various energy estimators that rely on different levels of knowledge and are modeling formally the problem of correct caching policy.

Experimental platforms and mobility

Performance evaluation of algorithms and protocols for wireless multihop networks has long been realized using simulators. If this approach is useful to evaluate some properties like algorithms convergence, scalability or their cost in control traffic, but it fails to give accurate performance evaluation, as they do not provide accurate models for radio propagation or operating systems-related effects. In sensor networks, several experimental platforms such as SensLab or WiseBed have been deployed these past years to overcome this limitation. These testbeds provide a limited support of mobility, though. In the FIT Equipex, we have built an experimental platform that includes several wheeled robots carrying sensors in an environment in which multiple fixed sensors are deployed. To control the robots mobility, an experimenter is able to specify mobility patterns, or to select state of the art patterns in a database. Besides, this platform is federated with cognitive radio and WLAN platforms and accessible to the whole research community, following the OneLab model. In parallel, the maintenance of the platform shall be as limited as possible, and robots mobility needs to be controlled and verified, for example to minimize collisions. That’s why we have proposed, in Yacine Benchaïb’s Ph.D, a simple domain specific language to describe mobility, called SILUMOD, based on SCALA. This language can be translated into mobility directives for the robots, or serve as an input for an emulation tool called VIRMANEL, which spawns virtual machines corresponding to the nodes and emulates their movements by tearing up and down firewall rules. Both tools are available online, released under the LGPL license. The next step was to link SILUMOD with formal verification tools to validate that mobility models do not lead to undesired situations.

Digital mobile identities and their environment

My research in this field started with my DEA (Masters degree) training period in the ReMaP INRIA team. Isabelle Guérin-Lassous and I designed a bandwidth reservation protocol (BRuIT – Bandwidth Reservation under InTerferences influence) that used information on long range interferences between signals (data flows for example) to accept or reject reservations. The objective of this protocol was to provide an accurate admission control mechanism in order to provide realistic reservations. BRuIT is composed of a reactive routing part, a local information transmission mechanism, and a reservation setup/tear-down mechanism. Information is obtained by the mobile nodes concerning their two-hops neighborhood and admission control (accepting or rejecting reservations) is made according to this information. When actually proposed protocols usually react by canceling or re-routing reserved flows when congestion appears in the network, our approach tries to avoid congestion appearance by rejecting unsuitable reservation requests. %The first version of this protocol was basic and lacked many features. First of all, performing an accurate network resource allocation is not always possible, especially in disconnected networks. Therefore, a reservation degradation mechanism is required in order to allow QoS flows to choose the congestion reaction politics. Should the reserved bandwidth be reduced or should the reservation be canceled when the bandwidth cannot be provided anymore ?

This work allowed us to identify several problematic scenarios in which network density or obstructions could impair reservations. We extended this work by identifying a basis of problematic situations leading to unfairness or even starvation, which we modeled using discrete time Markov chains. Subsequently, Isabelle Guérin-Lassous, Janez Žerovnik and I designed a distributed bandwidth allocation algorithm that improves fairness while maximizing the global bandwidth usage. I then proposed two other algorithms working directly at the medium access control layer to improve fairness in a more reactive way.